Which of the following statements about parquet storage format is false?Question 2Answera.Parquet storage format stores the schema with the data.b.Given a dataframe with 100 columns. It is faster to query a single column of the dataframe if the data is stored using the CSV storage format compared to parquet storage format.c.Given a dataframe with 100 columns. It is faster to query a single column of the dataframe if the data is stored using the parquet storage format compared to it being stored in a CSV storage format.d.Parquet storage format stores all values of the same column together.
Question
Which of the following statements about parquet storage format is false?Question 2Answera.Parquet storage format stores the schema with the data.b.Given a dataframe with 100 columns. It is faster to query a single column of the dataframe if the data is stored using the CSV storage format compared to parquet storage format.c.Given a dataframe with 100 columns. It is faster to query a single column of the dataframe if the data is stored using the parquet storage format compared to it being stored in a CSV storage format.d.Parquet storage format stores all values of the same column together.
Solution
The false statement about parquet storage format is:
b. Given a dataframe with 100 columns. It is faster to query a single column of the dataframe if the data is stored using the CSV storage format compared to parquet storage format.
Explanation: Parquet is a columnar storage file format. It is optimized for use with big data processing frameworks like Hadoop, Spark, etc. The main advantage of using Parquet over CSV is that it allows faster and more efficient querying of data. This is because it stores all values of the same column together, which allows for more efficient disk I/O and compression. So, querying a single column from a dataframe with 100 columns would be faster with Parquet storage format compared to CSV storage format.
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